Implementing FAIR in the Agricultural Research Federation

Dr Megan Wong

Federation University Australia

Kerry Levett

Australian Research Data Commons

CC BY 4.0 International

Box, P., Simons, B., Thompson, H., Macleod, A., David, R., Schneider, D., Watkins, D., Hergenhan, R., Gregory, L., Wilson, P., Taylor, N., Limmer, S.

Gillett, H., Simon Cox

www.agrefed.org.au

Autonomous data provider communities delivering data to an Agricultural Research Cloud

‘My data’

The data (so far)

• Rotational crop trials • Frost nursey trials • Soil moisture sensors and

networks • Weather station sensor

network • National soil data and services • Soil sample dataset

“Our FAIR data”

Sustained Federated Community(AgReFed)

External domain

authorities

Representation

Delegation

‘My data’ to ‘Our FAIR data’

www.agrefed.org.au

AgReFed space

Catalogue

PortalTechnical

Social

Data provider space

(Trusted) Repository

(Trusted) Repository

Web service

AgReFed FAIR Data AgReFed Trusted Repositories Governance policies

Technical policies

Policies

Trusted Repositories

FAIR Data

Alignment processes

Governance roles- Authority structures- Decision rights

Roles

Operational roles (e.g. Stewardship)

Data provisioning policies

UsersVocab

register

VocabService (RVA)

AgReFed – A socio-technical systemencompassing provider communities, roles, policies and alignment processes for enabling the discovery and (re)usability of agricultural data

Web service

Org. 1

Org. 2

Research Data Australia (RDA)

https://doi.org/10.25919/5cf179ba35db9Guidelines for Governance and Data stewardship:

www.agrefed.org.au

Individual provider space(my data and my organisation’s repository)

AgReFed cooperative space(Our collective data resource)

Provider Repositories

Data (and services)

AgReFed FAIR Data thresholds

(based on FAIR principles and incorporating maturity

models))

AgReFed Trusted Repository requirements (based on CoreTrustSeal

Data Repositories Requirements)

Alignment processes

Alignment processes and policies From ‘my data’ to Our FAIR data

AgReFed data and repository thresholds for alignment processes are

set through policies

Individual providers’ heterogeneous data and provisioning arrangements can be brought into alignmentwith agreed levels of FAIRness and repository trustedness

www.agrefed.org.au

AgReFed FAIR Data Policy

Qualifying thresholds:The green cells indicate the proposed minimum acceptable level that data must comply with before it can be ‘published’ as AgReFed Data

• Where different shades of green are shown, the lightest green indicates minimum acceptable level, and the darkest green indicates stretch goal

• AgReFed FAIR Data policy is based on the FAIR1 principles.

• The AgReFed FAIR Data Assessment is based on the ARDC FAIR Data Self-assessment Tool2. Modified based on user feedback to improve usability.

1: https://www.go-fair.org/fair-principles/ 2: https://ardc.edu.au/resources/working-with-data/fair-data/fair-self-assessment-tool/

www.agrefed.org.au

AgReFed FAIR Assessment - Findable

Principle (for AgReFed) Increasingly FAIR --> FINDABLE

Q1 The data product has been assigned (an) identifier(s) No identifier Local identifier Web address (URL)Globally unique, citable and persistent identifier (e.g. DOI, PURL, or Handle)

Q2 The data product identifier is included in all metadata records/files describing the data

No Yes

Q3 The data product is described by a metadata record The data is not described Brief title and descriptionBrief title and description, and multiple other fields filled out, albeit briefly.

Comprehensively (including all AgReFed required fields*) using a formal machine-readable metadata schema.

Q4 The data product is described by a metadata record that is indexed in a searchable registry or repository

The data is not described in any registry or repository

Local institutional repository Domain-specific repository Generalist public repository

Data is in one place but discoverable through several places (i.e. other registries, RDA, Google Data Search)

ACCESSIBLEINTEROPERABLEREUSABLE

www.agrefed.org.au

* Q3 - Minimum metadata requirements were specified. See https://doi.org/10.25919/5cf179ba35db9

AgReFed FAIR Assessment - Accessible

Principle (for AgReFed) Increasingly FAIR --> FINDABLEACCESSIBLE

Q5 How accessible is the data? The access method(s) must be explicitly stated in the metadata record, e.g. if any authentication is needed, or there are any restrictions to access.

No metadata record Access to metadata only

Unspecified access conditions e.g. "contact the data custodian to discuss access"

Embargoed access after a specified date; or A deidentified version of the data is publicly accessible

Fully accessible public, or to persons who meet and follow explicitly stated conditions and processes, e.g. ethics approval for sensitive data

Q6 Data are available for reuse via a standardised communication protocol, such as file download over https, or a web service.

No access to data By individual arrangementFile download from online location

Non-standard web service (e.g. OpenAPI/Swagger/informal API)

Standard web service API (e.g. OGC)

Q7 The repository/registry agrees to maintain the persistence of the metadata record, even if the data product is no longer available.

No (or not applicable, if no metadata record exists)

Unsure Yes

INTEROPERABLEREUSABLE

www.agrefed.org.au

AgReFed FAIR Assessment - InteroperablePrinciple (for AgReFed) Increasingly FAIR -->

FINDABLE

ACCESSIBLE

INTEROPERABLE

Q8 The data products are available in (an) open (file) format(s)Data are mostly available only in a proprietary format

Data are available in an open format

Data are available in an open, documented, widely-used standard format (i.e. NetCDF, CSV, JSON, XML, etc)

Q9 The data is machine readable (see Glossary for definition) The data are unstructuredThe data are structured and machine-readable (i.e. csv, JSON, XML, RDF, database files, etc)

Q10 The data are semantically interoperable, because they use standard, accessible ontologies and/or vocabularies to describe the data elements/variables.

Data elements are not described (i.e. fields or objects are labelled with codes or not at all)

Data elements are described (so that a human user can correctly interpret the data), but no standards have been used in the description

Recognised standards have been used in the description of data elements, but no published vocabularies with resolvable URIs

Published vocabularies using resolvable global identifiers linking to explanations are used, so that the data can be read and understood by machines as well as humans.

Q11 The relationships to other data and resources (e.g. related datasets, services, publications, grants, etc) are described in the metadata or data, to provide context around the data.

There are no links to other metadata or data

The metadata record includes URI links to related metadata, data and definitions

Qualified links to other resources are recorded in a machine readable format, e.g. a linked data format such as RDF

REUSABLE

www.agrefed.org.au

AgReFed FAIR Assessment - Reusable

Principle (for AgReFed) Increasingly FAIR -->

FINDABLE

ACCESSIBLE

INTEROPERABLE

REUSABLE

Q12 Machine-readable data licenses are assigned to each data product, and are stated in the metadata record.

No license is applied

Non-standard license applied, without a license deed URL encoded in a machine-readable format (e.g. RDF/XML) in the metadata record

Non-standard license applied, WITH the license deed URL encoded in a machine-readable format (e.g. RDF/XML) in the metadata record

Standard license applied (e.g. Creative Commons), without a license deed URL encoded in a machine-readable format (e.g. RDF/XML) in the metadata record

Standard license applied (e.g. Creative Commons), WITH the license deed URL encoded in a machine-readable format (e.g. RDF/XML) in the metadata record

Q13 The provenance of the data product is described in the metadata, i.e. project objectives, data generation/collection (including from external sources) and processing workflows.

No provenance information is recorded

Partially recordedComprehensively recorded in a text format (i.e. TXT or PDF)

Comprehensively recorded in a machine readable format (i.e. in metadata record's schema or PROV, or in RDF, JSON, NetCDF, XML, etc)

Q14 The preferred citation for the data product is provided in metadata record

NoCitation does not include identifier

Citation includes identifier

www.agrefed.org.au

• Easy wins – creating and improving metadata records

• A bit harder• Structuring data for accessibility – needed some support

• e.g. Unstructured spreadsheets into databases• e.g. Integrating multiple data types

• Storage and delivery options - multiple solutions to suit the research groups’ everyday business and institutional support• Data and metadata standards used where possible

• Hardest – Semantic interoperability!• Controlled vocabularies: Stretch goal for research groups, achievable for data providers in soils

• Variation in incentives/disincentives for providing data and making it FAIR

• Variations in institutional support and resourcing

Experience of making data FAIR

www.agrefed.org.au

Not so FAIR FAIR

On the experience of making data and services FAIRer using the FAIR data assessment:

“Incredibly useful”

“Helped us understand what FAIR is and how important it is to data”

“At a conference I advocated for FAIR data to help advance (agricultural) research”

“The process has increased my knowledge of FAIR. How FAIR is FAIR and how FAIR you want it to be? The benchmarking and levels have been good. No tool is perfect”

“We were doing a good job around Interoperability, and this process showed us how we could easily improve Findability and Accessibility.”

“Improving accessibility to our services……the FAIR tool certainly helped”

(re. institutional data plan) “We are not using a FAIR assessment tool, but probably could”

“Quite subjective. But reassessment was easier because FAIR tool had been updated, and made more nuanced.”

www.agrefed.org.au

Suggestions for improvement Repeatability as an assessment tool

“A little ambiguous. I’d give different answer on a different day. Sitting and doing it with you helped me dig a little deeper regarding how to answer the questions”

“Making the FAIR tool a bit FAIRer! Capturing the answers as metadata”

What is being assessed and why“Guidance for providers to decide and describe what data products needed to be assessed and why; for example, services, collections, or individual datasets”“Helping partners understand what they are assessing and why is still a bit of a challenge”

Interpretation “It would be good for online tool to save results; and spit out suggestions for how to make the dataset FAIRer”“Some more info around FAIR vs Open”

Support needed“Definitely needed ARDC assistance to complete - needs examples of different levels of FAIRness to be clearer.”“Essential to have one-on-one time with someone who really understands the FAIR process, and who also can understand the research process/topic.”“Difficult when data scientists (or data managers) and researchers don't speak the same language, to get the right info out of each other.”

How FAIR is FAIR, How FAIR do we want it to be?..........

www.agrefed.org.au

Incorporating FAIR settings into AgReFed policy and processes

https://doi.org/10.25919/5cf179ba35db9

Guidelines for Governance and Data stewardship:

www.agrefed.org.au

“How FAIR is FAIR?”

• Tested and further developed within the socio-technical framework of AgReFed

• How it works for provider communities,

• How it is implemented and works with roles, processes and other policies (e.g. Membership Policies, Strategic Policies, Data Steward role)

“Our FAIR data”

UNE Smart Farms National soil data and information ARC Centre of Excellence

in Plant Energy Biology

School of Agriculture Food and Wine

Waite Research Institute

Australian Plant PhenomicsFacility

CSIRO Environmental informatics

Project Support and Stewardship Leads:

Centre for eResearch and Digital Innovationand

Participating partners:

This project is supported by the Australian Research Data Commons (ARDC). The ARDC is enabled by NCRIS.

www.agrefed.org.au